YOLOv8 vs YOLOv11: Model Comparison

Choosing the right YOLO model can be tricky — should you prioritize speed or accuracy? 🚀 In this video, we compare YOLOv8 and YOLOv11 side by side to help you find the perfect model for your object detection projects. You’ll see: Real inference speed comparisons (ms/frame) Object detection accuracy across YOLO-N, YOLO-S, YOLO-M, and YOLO-L models Visual graphs and results using real-world traffic videos How each model performs across different frame rates and environments By the end of this video, you’ll know exactly which YOLO model suits your specific use case — whether it’s for real-time detection, edge deployment, or high-accuracy AI pipelines. Resources: Check our Blog: https://www.labellerr.com/blog/yolo11... Labellerr’s GitHub:https://github.com/Labellerr/Hands-On... Notebook:https://github.com/Labellerr/Hands-On... Chapters: 0:00 Introduction: Choosing the Right YOLO Model 0:50 YOLO Model Comparison Notebook Overview 1:04 Step 1: Importing Classes & YOLOComparator 1:26 Comparing YOLO V8 Models (N, S, M, L) 2:06 Analysis: YOLO V8 Model Results 3:02 Speed vs. Accuracy Trade-off in YOLO V8 4:29 Comparing YOLO V11 Models (N, S, M, L) 6:23 Analysis: YOLO V11 Model Results 7:18 Graph Comparison: Inference Time & FPS 8:30 Direct Comparison: YOLO V8N vs. V11N 9:50 Performance Analysis: V8N vs. V11N 11:13 Direct Comparison: YOLO V8L vs. V11L 11:56 Graph & Performance Analysis: V8L vs. V11L 12:54 Summary: Model Recommendations 13:17 GitHub Repository & Additional Resources Interested in learning more about our services? Website: https://www.labellerr.com Book a Demo: https://www.labellerr.com/book-a-demo Find us on Social Media Platforms: LinkedIn:   / labellerr   Twitter: https://x.com/Labellerr1 #YOLO #YOLOv8 #YOLOv11 #ObjectDetection #ComputerVision #MachineLearning #DeepLearning #AI #AIAgent #ModelComparison #TechTutorial #DataScience #YOLOComparison #AIProject #NeuralNetworks #VisionAI #OpenSourceAI #ArtificialIntelligence #Python #AIResearch